一类新的模糊神经网络及其在系统建模中的应用

Proceedings of SOUTHEASTCON '94 Pub Date : 1994-04-10 DOI:10.1109/SECON.1994.324333

H. Ma, A. El-Keib, X. Ma

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引用次数: 1

摘要

本文提出了一类新的模糊神经网络及其在系统建模中的应用。对于给定的样本数据集，可以识别出最优的模糊关联记忆规则集和权重集。非线性系统建模的实验结果表明，所提出的模糊神经网络可以准确地对复杂的非线性系统进行建模，并且模型具有很强的鲁棒性，其建模精度对样本数据不敏感。

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A new class of fuzzy neural networks with application in system modeling

This paper presents a new class of fuzzy neural networks and its application to system modeling. The optimal set of fuzzy associative memory rules and weights can be identified for a given set of sample data. Test results of modeling a nonlinear system show that the proposed fuzzy neural network can accurately model a complicated nonlinear system and the model is quite robust in the sense that its modeling accuracy is much insensitive to sample data.<>

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Proceedings of SOUTHEASTCON '94

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